Mental models for understanding complex, interconnected systems. Feedback loops, emergence, leverage points, and bottlenecks.
Mental models for understanding complex, interconnected systems. Feedback loops, emergence, leverage points, and bottlenecks.
Browse all mental models in this discipline below.
Consider not just the immediate consequences of a decision, but the consequences of those consequences.
Every system has outputs that feed back into inputs — reinforcing or balancing the system's behaviour over time.
Some things don't just survive shocks — they get stronger from them. Position yourself to benefit from disorder.
In any system, there are specific places where a small change produces disproportionately large effects.
Complex behaviour arises from simple rules followed by many agents — the whole is genuinely different from the sum of its parts.
Some processes need a minimum threshold of input before anything happens — then they suddenly accelerate.
When a measure becomes a target, it ceases to be a good measure.
Well-intentioned interventions often produce the opposite of their intended effect when people respond strategically to new incentives.
Some complexity is inherent to the problem. Some is created by the solution. Learning to tell the difference is a superpower.
Every system has one constraint that limits overall throughput. Improving anything else is waste until you fix the bottleneck.
In complex systems, tiny changes in initial conditions can produce vastly different outcomes.
Economic progress requires old industries and methods to be destroyed by new ones. The process is painful but essential for growth.
In some distributions, extreme events are far more common than normal distributions predict. The tails are 'fat' — and that's where the real action is.
Imagine all possible strategies as points on a landscape where height represents fitness. Evolution (and innovation) climbs toward peaks — but can get stuck on local hills.
Systems resist change and try to return to their equilibrium state — even when change would be beneficial.
The state of a system depends on its history, not just its current inputs. Damage doesn't always reverse when you remove the cause.
Sometimes the intervention causes more harm than the problem. The cure can be worse than the disease.
Some products become more valuable as more people use them — creating winner-take-all dynamics.
Where you end up depends heavily on where you started and the sequence of steps taken — not just the destination's inherent qualities.
In many systems, a small number of inputs produce the vast majority of outputs. Distributions are rarely equal.
Build slack into systems. The backup you never use isn't waste — it's insurance against the failure you can't predict.
Imagine multiple futures, not just one. Prepare for several plausible outcomes rather than betting everything on a single prediction.
Any component whose failure causes the entire system to fail. The question isn't whether it will fail — it's whether you've prepared for when it does.
The longer something has survived, the longer it's likely to continue surviving. Age is a positive signal for ideas and systems.
When everyone has access to a shared resource and acts in self-interest, the resource gets depleted.
Some problems have no definitive formulation, no stopping rule, and no test for a solution. Recognising them changes how you approach them.